scholarly journals Web User Trust Evaluation: A Novel Approach Using Fuzzy Petri Net and Behavior Analysis

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1487
Author(s):  
Zenan Wu ◽  
Liqin Tian ◽  
Yi Zhang ◽  
Zhigang Wang
Keyword(s):  
Petri Nets ◽  
Online Shopping ◽  
User Behavior ◽  
Online Banking ◽  
Trust Evaluation ◽  
Trust Value ◽  
Direct Trust ◽  
Fuzzy Petri Nets ◽  
System Resilience ◽  
User Trust

With the development of society and information technology, people’s dependence on the Internet has gradually increased, including online shopping, downloading files, reading books, and online banking. However, how to ensure the safety and legitimacy of these network user behaviors has become the focus of attention. As we all know, cybersecurity and system resilience originate from symmetry. Due to the diversity and unpredictability of cyber-attacks, absolute cybersecurity is difficult to achieve; system resilience indicates that protecting system security should shift from resisting attacks to ensuring system continuity. The trust evaluation of network users is a research hotspot in improving network system security. Aiming at the defects of incomplete evaluation processes and inaccurate evaluation results in current online user behavior trust evaluation methods, this paper combines the basic principles of online user trust evaluation and proposes a trust evaluation model that combines fuzzy Petri nets with user behavior analysis. First, for “unfamiliar” users, we used fuzzy Petri nets to calculate the user’s recommended trust value as the system’s indirect trust value; next, we used the user’s behavior record as evidence to conduct direct trust evaluation on the user to obtain the system’s direct trust in the user’s value; finally, the two calculation results were combined to obtain the user’s comprehensive trust value. In terms of experimental verification, the experimental data came from a self-developed e-book management system. Through theoretical analysis and simulation results, it was shown that the model met the optimization conditions of subjective and objective relative balance, the evaluation process was more complete, and the trust evaluation values of network users could be obtained more accurately. This evaluation method provides solid theory and research ideas for user credibility judgment of key network basic application platforms such as online shopping malls, online transactions, and online banking.

scholarly journals Personalized project recommendations: using reinforcement learning

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Faxin Qi ◽  
Xiangrong Tong ◽  
Lei Yu ◽  
Yingjie Wang
Keyword(s):  
Reinforcement Learning ◽  
User Behavior ◽  
Collaborative Work ◽  
Recursive Least Squares ◽  
The Internet ◽  
Dynamic Impact ◽  
Rls Algorithm ◽  
Trust Value ◽  
Q Learning ◽  
Actual Evaluation

AbstractWith the development of the Internet and the progress of human-centered computing (HCC), the mode of man-machine collaborative work has become more and more popular. Valuable information in the Internet, such as user behavior and social labels, is often provided by users. A recommendation based on trust is an important human-computer interaction recommendation application in a social network. However, previous studies generally assume that the trust value between users is static, unable to respond to the dynamic changes of user trust and preferences in a timely manner. In fact, after receiving the recommendation, there is a difference between actual evaluation and expected evaluation which is correlated with trust value. Based on the dynamics of trust and the changing process of trust between users, this paper proposes a trust boost method through reinforcement learning. Recursive least squares (RLS) algorithm is used to learn the dynamic impact of evaluation difference on user’s trust. In addition, a reinforcement learning method Deep Q-Learning (DQN) is studied to simulate the process of learning user’s preferences and boosting trust value. Experiments indicate that our method applied to recommendation systems could respond to the changes quickly on user’s preferences. Compared with other methods, our method has better accuracy on recommendation.

The Internet according to kids

2002 ◽  
Vol 3 (2) ◽  
pp. 45-52
Author(s):  
Jorian Clarke
Keyword(s):  
Parental Involvement ◽  
Mobile Phones ◽  
Online Shopping ◽  
Online Banking ◽  
Internet Usage ◽  
The Internet ◽  
The Future ◽  
Child Friendly ◽  
Over Time

Describes a six‐year study of children’s Internet usage which shows how preferences and habits have changed over time; this was conducted by SpectraCom Inc and Circle 1 network. Explains the research methodology and the objectives, which were to identify trends in the amount of time spent by children online now and in future, their opinions about the future role of the Internet in society and the future of e‐commerce, and parents’ roles in children’s online activities. Concludes that there is need for a more child‐friendly content in Internet sites and for more parental involvement, that children will be influential in the market for alternative devices like mobile phones, that online shopping is likely to flourish, and that children have a growing interest in online banking.

A self-navigating robot using Fuzzy Petri nets

2018 ◽  
Vol 101 ◽  
pp. 153-165 ◽  
Author(s):  
Seung-yun Kim ◽  
Yilin Yang
Keyword(s):  
Petri Nets ◽  
Fuzzy Petri Nets

scholarly journals Robust and Accurate Trust Establishment Scheme for Wireless Sensor Network

2020 ◽  
Vol 12 (6) ◽  
pp. 14-29
Author(s):  
Audrey NANGUE ◽  
◽  
Elie FUTE TAGNE ◽  
Emmanuel TONYE
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Trust Management ◽  
Wireless Sensor ◽  
Management Systems ◽  
Trust Value ◽  
Direct Trust ◽  
Indirect Trust

The success of the mission assigned to a Wireless Sensor Network (WSN) depends heavily on the cooperation between the nodes of this network. Indeed, given the vulnerability of wireless sensor networks to attack, some entities may engage in malicious behavior aimed at undermining the proper functioning of the network. As a result, the selection of reliable nodes for task execution becomes a necessity for the network. To improve the cooperation and security of wireless sensor networks, the use of Trust Management Systems (TMS) is increasingly recommended due to their low resource consumption. The various existing trust management systems differ in their methods of estimating trust value. The existing ones are very rigid and not very accurate. In this paper, we propose a robust and accurate method (RATES) to compute direct and indirect trust between the network nodes. In RATES model, to compute the direct trust, we improve the Bayesian formula by applying the chaining of trust values, a local reward, a local penalty and a flexible global penalty based on the variation of successful interactions, failures and misbehaviors frequency. RATES thus manages to obtain a direct trust value that is accurate and representative of the node behavior in the network. In addition, we introduce the establishment of a simple confidence interval to filter out biased recommendations sent by malicious nodes to disrupt the estimation of a node's indirect trust. Mathematical theoretical analysis and evaluation of the simulation results show the best performance of our approach for detecting on-off attacks, bad-mouthing attacks and persistent attacks compared to the other existing approaches.

Dynamic Monitoring in Ad Hoc Network

2012 ◽  
Vol 229-231 ◽  
pp. 1481-1486 ◽  
Author(s):  
Honarbakhsh Shohreh ◽  
Zamani Mazdak ◽  
Honarbakhsh Roza
Keyword(s):  
Delay Time ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Dynamic Monitoring ◽  
Trust Evaluation ◽  
Trust Value ◽  
Novel Model

This paper, present a novel model to resolve the problems of evaluating trust value of nodes, and prepare a dynamic supervising in ad hoc network as well. Trust evaluation is not only based on direct interactions among nodes, but also observing previous behaviors of nodes, which come from all interactions through the network. This model specially decreases the delay time of selecting a new head for each cluster, which leads to prepare a dynamic monitoring in intra cluster and inter cluster in ad hoc network.

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